Web Research Specialist

What You'll Do6

• Construct natural-language research questions that start from a verifiable fact and make that fact difficult for AI agents to locate.
• Create clusters of independently checkable clues spanning dates, people, places, organizations, works, events, records, and quantities, each with specific constraints.
• Run the obvious searches yourself and document the results in a validation record that proves the question is hard.
• Cite exact pages, tables, and sections from primary records found in government and institutional databases, archives, and registries.
• Maintain a structured evidence trail for every question, since documentation makes up the majority of the work.
• Research unfamiliar subjects from scratch using open-web methods when no prior domain knowledge exists.

Requirements8

• Master's degree or more than 3 years of equivalent work experience.
• Demonstrated open-web research ability, including locating primary records and navigating government databases, archives, registries, and PDF documents.
• Precision with sourcing: cite exact pages, tables, and sections, not just homepages.
• Comfort researching unfamiliar subjects from scratch.
• Native or near-native written English.
• High tolerance for structured documentation, with the evidence trail as the core deliverable.
• Prior experience with LLM evaluation, red-teaming, or benchmark construction.
• Domain experience in at least one of: reference librarianship, investigative journalism, fact-checking, OSINT, due diligence, KYC, patent search, legal discovery, genealogy, or competitive quizzing.

Who Should Apply

The ideal candidate is a trained researcher who enjoys the hunt: someone from a reference librarian, investigative journalist, OSINT analyst, or fact-checker background who regularly digs through primary records and government databases. This role suits people who find satisfaction in documenting every search step, not just delivering an answer. It is less suitable for subject matter experts who want to write content or answer questions in their own field, and for writers who dislike rigid evidence trails. Common reasons candidates score low include citing vague sources such as homepages instead of exact pages or tables, and failing to show retrieval depth when the topic sits outside their specialty.